Affordable housing for threshold households in European major cities

Contrary to many forecasts, some major German cities are currently growing again or still raising. However, this growth confronts the cities with enormous challenges. In addition to growing pressure on infrastructural supply, demand for housing is rising. The result: the prices for housing are increasing rapidly.

This high rental price level in cities makes it difficult for low-income households to afford adequate and sufficient living space on their own. In cities with above-average rent levels middle-income households are increasingly affected, although they do not get financial support like housing allowance. Percentage of housing costs in total monthly income is very high – partly over 30%. So, these households can be counted to so-called threshold households in Germany.

This paper deals with the research question, how much income a household would need in order to afford adequate housing in the examined cities. Therefore, a model is developed which allows a calculation for the most affected household types: single, couple without children, couple with child/children & single parent with child/children. Beneath, some sub-questions should be answered by this model calculation: What is the number of households in the surveyed cities whose monthly expenditure is above the 30% threshold? And what is their spatial distribution over the urban area – are there quarters, which are highly affected? Data on purchasing power and social milieus as well as information on supply and stock rents should serve as a data basis for answering these questions.

In addition, it will be determined how the calculated net household incomes (for the four household types) can be reconciled with the statutory income limits of municipal programs for the promotion of affordable housing. Are the established income limits sufficient or need to be adjusted?

The results are compared with data from Sweden – in Sweden, more data is available at all. In Swedish cities, such as Stockholm or Gothenburg, rents are also increasing due to rising demand.

The availability and quality of data on the different administrative levels will be analysed and discussed conclusively. Does a better data basis provide more possibilities for adjusting subsidies?

Results will be a model and a better understanding of threshold households in different cities.